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Augmented-Nature

ProteinAtlas MCP Server

get_brain_expression

Retrieve brain region expression data for proteins to analyze tissue-specific protein distribution using Human Protein Atlas information.

Instructions

Get brain region expression data for a protein

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geneYesGene symbol
formatNoOutput format (default: json)

Implementation Reference

  • The main handler function for the 'get_brain_expression' tool. Validates input using isValidGeneArgs, fetches brain expression data via fetchBrainExpression, and returns formatted JSON response or error.
    private async handleGetBrainExpression(args: any) {
      if (!isValidGeneArgs(args)) {
        throw new McpError(ErrorCode.InvalidParams, 'Invalid gene arguments');
      }
    
      try {
        const result = await this.fetchBrainExpression(args.gene);
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(result, null, 2),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `Error fetching brain expression: ${error instanceof Error ? error.message : 'Unknown error'}`,
            },
          ],
          isError: true,
        };
      }
    }
  • src/index.ts:522-533 (registration)
    Tool registration in the listTools response, including name, description, and input schema definition.
    {
      name: 'get_brain_expression',
      description: 'Get brain region expression data for a protein',
      inputSchema: {
        type: 'object',
        properties: {
          gene: { type: 'string', description: 'Gene symbol' },
          format: { type: 'string', enum: ['json', 'tsv'], description: 'Output format (default: json)' },
        },
        required: ['gene'],
      },
    },
  • Input schema defining parameters for the get_brain_expression tool: required 'gene' string and optional 'format'.
    inputSchema: {
      type: 'object',
      properties: {
        gene: { type: 'string', description: 'Gene symbol' },
        format: { type: 'string', enum: ['json', 'tsv'], description: 'Output format (default: json)' },
      },
      required: ['gene'],
    },
  • Helper method that performs the API query to Human Protein Atlas with specific columns for brain tissue expression data.
    private async fetchBrainExpression(gene: string): Promise<any> {
      const columns = ['g', 'eg', 'rnabrs', 'rnabrd', 'rnabrss', 'brain_RNA_amygdala', 'brain_RNA_cerebellum', 'brain_RNA_cerebral_cortex', 'brain_RNA_hippocampal_formation', 'brain_RNA_hypothalamus'];
      return this.searchProteins(gene, 'json', columns, 1);
    }
  • Input validation helper function used by get_brain_expression and similar tools to validate gene and optional format arguments.
    const isValidGeneArgs = (
      args: any
    ): args is { gene: string; format?: string } => {
      return (
        typeof args === 'object' &&
        args !== null &&
        typeof args.gene === 'string' &&
        args.gene.length > 0 &&
        (args.format === undefined || ['json', 'tsv', 'xml', 'trig'].includes(args.format))
      );
    };
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't cover important traits like whether it's a read-only operation, potential rate limits, error handling for invalid genes, or the structure of the returned data. This leaves gaps for an AI agent to understand operational constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy for an AI agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned expression data includes (e.g., numerical values, brain region names, statistical metrics) or how to interpret results. For a tool with 2 parameters and no structured output guidance, more context is needed to ensure proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear documentation for both parameters ('gene' as a gene symbol and 'format' as an output format with enum values). The description doesn't add extra meaning beyond the schema, such as examples of valid gene symbols or implications of choosing 'tsv' over 'json', but the schema provides adequate baseline information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('brain region expression data for a protein'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_tissue_expression' or 'get_blood_expression', which might offer similar expression data for different biological contexts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'get_tissue_expression' or 'compare_expression_profiles'. The description lacks context about prerequisites, such as needing a valid gene symbol, or when this tool is preferred over others for brain-specific queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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